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VIČAR, T. -- RAUDENSKÁ, M. -- GUMULEC, J. -- BALVAN, J. The Quantitative-Phase Dynamics of Apoptosis and Lytic Cell Death. Scientific Reports. 2020. v. 10, no. 31 January, ISSN 2045-2322. URL: https://doi.org/10.1038/s41598-020-58474-w

Original name:
The Quantitative-Phase Dynamics of Apoptosis and Lytic Cell Death
Czech name:
Written by (author):
Department:
Department of Chemistry and Biochemistry
Kind of publication:
article in a professional periodical
Periodical:
Scientific Reports
Nature of article:
paper
Volume no. (year):
10
Periodical number within the volume:
31 January
Year of publication: 2020
Starting page:
Up to page:
Number of pages:
12
Sub-specification:
článek je obsažen v databázi Web of Science
UT code by Web of Science:
EID code by Scopus:
Form of publication:
printed version
Original language:
English
Description in original language:
Cell viability and cytotoxicity assays are highly important for drug screening and cytotoxicity tests of antineoplastic or other therapeutic drugs. Even though biochemical-based tests are very helpful to obtain preliminary preview, their results should be confirmed by methods based on direct cell death assessment. In this study, time-dependent changes in quantitative phase-based parameters during cell death were determined and methodology useable for rapid and label-free assessment of direct cell death was introduced. The goal of our study was distinction between apoptosis and primary lytic cell death based on morphologic features. We have distinguished the lytic and non-lytic type of cell death according to their end-point features (Dance of Death typical for apoptosis versus swelling and membrane rupture typical for all kinds of necrosis common for necroptosis, pyroptosis, ferroptosis and accidental cell death). Our method utilizes Quantitative Phase Imaging (QPI) which enables the time-lapse observation of subtle changes in cell mass distribution. According to our results, morphological and dynamical features extracted from QPI micrographs are suitable for cell death detection (76% accuracy in comparison with manual annotation). Furthermore, based on QPI data alone and machine learning, we were able to classify typical dynamical changes of cell morphology during both caspase 3,7-dependent and -independent cell death subroutines. The main parameters used for label-free detection of these cell death modalities were cell density (pg/pixel) and average intensity change of cell pixels further designated as Cell Dynamic Score (CDS). To the best of our knowledge, this is the first study introducing CDS and cell density as a parameter typical for individual cell death subroutines with prediction accuracy 75.4% for caspase 3,7-dependent and -independent cell death.
Description in English:
Description in Czech:
Year of submission: 2020
Year of transmission:
RIV identification number:
URL:
https://doi.org/10.1038/s41598-020-58474-w
 
Entry made by: Markéta Hejčová, DiS.
Last change:
06/04/2020 11:20 (Markéta Hejčová, DiS.)

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Source specification:

Scientific Reports. London: ISSN 2045-2322.

Original name:
Scientific Reports
Czech name:
Written by (author):
Kind of publication:
magazine
ISSN:
2045-2322
Country of publisher:
United Kingdom of Great Britain and Northern Ireland
Place of publishing:
London
Publisher: Nature publishing group
URL: http://www.nature.com/srep/
Reviewed magazine:
no
Original language:
English
Description in original language:
Description in English:
Description in Czech:
 
Entry made by:
Last change: 11/09/2016 11:10 (Šárka Novotná)

Evaluation of publication:

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